The hallmark of human cancer is heterogeneity. The heterogeneity of human cancer can be demonstrated in at least three aspects: diverse histopathological characteristics, different genetic traits, and complex molecular events and signaling mechanisms. These factors reflect the complexity of the underlying molecular mechanisms governing carcinogenesis and carcinoma progression. Therefore, these factors contributing to heterogeneity also impose great challenges in designing effective therapeutic strategies to benefit cancer patients.
To tackle this challenge, it is critical to take innovative approaches to identify patient subgroups that share common molecular characteristics. This approach would further provide frameworks to assist in developing rational cancer diagnostics and therapeutic strategies. One of the best examples is the development of trastuzumab in treating Her2 positive breast cancers. Her2 is a growth promoting oncogene over-expressed in approximately 18% of breast cancer patients. A substantial body of work, including those using genome-scale gene expression measures, has demonstrated that Her2 positive breast cancer is a distinct disease entity which is distinctive in phenotypic behaviours such as the tendency for distant metastasis. Trastuzumab, a monoclonal antibody against Her2, has been shown to be an effective treatment only for breast cancer patients that show Her2 amplification. Another example is the discovery of the positive correlation between EGFR mutation and the response to EGFR inhibitor Iressa in treating non-small cell lung cancer patients.
Innovations like these have not been rapidly and successfully translated to other cancer types. For example, the therapeutic innovation for epithelial ovarian cancer (EOC) is slow. One major reason for this slow innovation for novel therapeutics in EOC is the lack of strong evidence supporting the applicability of patient stratification by using robust molecular diagnostics in the prediction of survival or therapeutic response. The heterogeneity of EOC might be even more complex which can be evident in at least four aspects.
Firstly, EOC represents a broad and heterogeneous entity which includes different invasive behavior (low malignant potential and invasive) as well as four major distinct histopathological subtypes, serous, mucinous, endometrioid, and clear cell carcinomas.
Secondly, EOC can occur in women harboring germline mutations of genes such as BRCA1/2 and mismatch repair genes as the hereditary trait, and in women without germline mutations as the sporadic trait.
Thirdly, the carcinogenesis process of EOC does not follow the step-wise model as in the colorectal cancer but rather has been proposed to follow two pathways: Type I and Type II. Type I diseases consist mainly of low-grade tumors with frequent KRAS or BRAF mutations and identifiable pre-malignant lesions (borderline malignancy). Type II diseases consist of high-grade tumors with predominant p53 mutations and potential precursor lesions harboring the same p53 mutations.
Finally, multiple signaling pathways contribute to growth promotion, insensitivity to antigrowth signals, inhibition of apoptosis and immune surveillance, enhanced angiogenesis, and promotion of invasion and metastasis in EOC. However, most EOC patients receive the same taxene/platinum-based chemotherapy regardless of the existing heterogeneity. For EOC, targeted therapies against VEGF (angiogenesis), EGFR (survival), or c-Kit (stem cell) pathways have not provided encouraging results from clinical trials. Therefore, the therapeutic modalities for EOC have remained at the primitive ground and have not provided additional benefits to the patients.
Genome-scale expression data has been utilized to characterize the complex biological diversity in human cancer. The substantial number of data points provides the robustness to detect not only common properties but also subtle biological differences across the whole variety of cancer samples. Several studies on breast cancer, glioblastoma multiforme (GBM), and diffuse large B-cell lymphoma have demonstrated this application on identifying patient subtypes.
Subtypes identified through expression microarray analyses are well linked with multiple important clinical parameters such as age, expression patterns of molecular markers, and patient survival prognosis. These efforts have helped advancing the understanding of cancer heterogeneity and designing potential diagnostic and therapeutic schemes which have made personalized medicine possible. For cancers that have not benefited from these advances, such as EOC, several microarray studies have been conducted to correlate the expression pattern with clinical features such as histological types, aggressiveness and patient outcomes. These studies have shed light that molecular subtyping might be able to provide hope of innovations in therapies for complex diseases such as EOC.
There have been accumulative evidences suggesting that epithelial-mesenchymal transition (EMT), a fundamental mechanism in embryonic development, plays a crucial role in promoting carcinoma progression. EMT describes the process driving epithelial cells to form cells exhibiting a fibroblastic-like morphology (mesenchymal). This mechanism involves multiple steps including the loss of an apico-basolateral polarity. The loss of epithelial cell polarity is induced by the dissolution of junctional complexes (desmosomes and adherens junctions) and tight junctions, and the concomitant remodeling of the actin cytoskeleton. Epithelial cells also delocalize polarity gene products and modulate their integrin adhesome to favor cell substrate adhesions to eventually acquire a mesenchymal phenotype. This critical transdifferentiation program leads to cells with low intercellular adhesion and equipped with rear-front polarity favoring cell locomotion and invasion.
In cancer progression, EMT explains how carcinoma cells invade and metastasize by transforming the epithelial state via an intermediate potentially metastable state to the mesenchymal state. The EMT program could also contribute to the dissemination of carcinoma cells from solid tumors and to the formation of micrometastatic foci which subsequently develop into clinically detectable metastases. EMT is also involved in the acquisition of chemoresistance maintaining cancer stemness and causing immune escape. The proof of concept that EMT indeed is involved in human cancers arises from several recent genome-scale expression analyses. EMT signatures have been found in the claudin-low (Basal B) subtypes of breast cancers, a subgroup of GBM, and the C1 and C5 clusters of EOC. In EOC, the progression and dissemination have been suggested to involve a vicious EMT-MET cycle.
Unique features of ovarian carcinoma are the ability to spread by shedding from the primary tumour to the surrounding peritoneal cavity and to generate large amount of ascites. The shedding of ovarian carcinoma cells requires the loss of cell-cell and cell-matrix adhesions. The production of ascites is mainly due to increased vascular permeability and extravasation of the intravascular fluid to the peritoneal cavity resulting from the presence of angiogenic factors such as VEGF. Some of the shed cells escape from apoptosis and survive as aggregates and form floating spheroids in the ascitic fluids. Cytokines and growth factors (ex. IL-6, IL-8, HB-EGF, TGF-α, VEGF, b-FGF, LPA, etc.) secreted from the cancer spheroids, reactive immune cells, and peritoneal mesothelial cells provide an autocrine and paracrine milieu for the survival of spheroids. These spheroids then adhere to and invade the peritoneum resulting in extensive dissemination of the disease. Transcriptional repressors such as SNAI1 and SNAI2 have been shown to govern the EMT process in ovarian cancer cells. Recent data have also demonstrated that pathway related to EMT is associated with platinum-based chemotherapy resistance (Helleman, Smid et al. 2010). Also, EMT is also related to a “migratory cancer stem cell-like” phenotype in recurrent ovarian cancers. In GBM, a mesenchyme like subtype was found by unsupervised clustering but not extensively. In breast cancer, several molecular subtypes are exhibiting a mesenchymal like phenotype. They include a newly described subtype named claudin-low. The basal subtype is also a mesenchymal-like phenotype; it includes sporadic tumors, BRCA1 tumors and sarcomatoid carcinoma.
EMT is best demonstrated at the tumor invasive fronts of colorectal cancers where in-transit mesenchymal-like cells can be identified. The invasive fronts indicate the interface between the main tumor mass and the microenvironment milieu. This frontline can be regarded as the starting point of the pressure gradient generated by the microenvironment. Signals of EMT thus follow a gradient from the invasive front toward the inner tumor mass. Also, within the inner tumor mass, pressures coming from hypoxia and nutrient depletion create another gradient for EMT. Therefore, EMT contributes to tumor heterogeneity. In fact, the different degree of EMT involvement provides a novel aspect to understand tumor heterogeneity that each individual tumor can be regarded as a mixture of different populations with or without undergoing EMT. The heterogeneity of each individual tumor is summarized in FIG. 1 and represented as an EMT Status (or EMT Score).
EMT can be triggered by different signal transduction pathways, including a large number of cell surface receptors like receptor tyrosine kinases, integrins, TGF-β receptors, as well as several intracellular kinases such as ILK and SRC. Most of the known inhibitors of these signaling pathways (e.g. Erlotinib, Dasatinib, Vatalanib, Sunitinib, etc.) were not originally identified based on their involvement on EMT regulation, but often as anti-proliferative agents. Anti-proliferation or growth inhibition has long been adopted as the standard endpoint for anti-cancer drug screen. Therefore, the current paradigm in cancer treatment still focuses on the discovery and development of cytotoxic therapeutic agents that alter the 5 hallmark mechanisms of cancer proposed by Hanahan and Weinberg (Hanahan and Weinberg, 2011, Cell, vol. 144, no. 5, pp. 646).
Experimental systems, whether in vitro cancer cell lines or tumor xenografts, have been established to fulfill that purpose. The development of the US National Cancer Institute (NCI) 60 human tumour cell line (NCI60) which includes nine distinct tumour types: leukaemia, CNS, renal, melanoma, ovarian, breast and prostate, has served as a great asset for cancer researchers to provide an in vitro model for drug discovery by identifying compounds with growth-inhibitory effects.
However, experiences from treatment failure of cytotoxic drugs suggested that incorporating other biological mechanisms which regulate tumour invasiveness and dissemination as additional endpoints might help design novel therapeutics to overcome resistance. In fact, an increasing number of studies that have demonstrated failure of established drugs in arresting cancer progression at its invasive phase have indirectly highlighted the importance of EMT control. One study identified potential cytotoxic agents against breast cancer cells that have undergone EMT. To our knowledge, there has been no drug-screen platform reported to solely inhibit EMT and achieve phenotype reversion without altering cell proliferation.
An important aspect of the development of a scheme targeting EMT phenotype is to establish a framework of facilitating the use of experimental systems, whether in vitro cell lines or xenografts, to incorporate into the subtype identification of in vivo cancers to model the reality in human. Cancer cell line collections such as breast cancer have been shown to retain their subtype characteristics corresponding to those of the in vivo counterparts and these cell lines have been demonstrated as powerful tools to model heterogeneity in cancer in vitro.
It has been shown that the gene expression profiles and genomic signatures of NCI60 have been further utilised to identify phenotype-specific drugs. The gene expression signature of NCI60 incorporated with the drug sensitivity results from over 40,000 compound screens have effectively identified targets not only with selectivity to the RAS and PI3K pathways but also with disease specificity to breast cancer subtypes (basal vs. luminal). This shows that oncogenomic data derived from a mixed assembly of cancer cell lines can be robust to provide valid therapeutic leads which are disease or phenotype specific, which further supports the possibility to establish a diagnostic-therapeutic framework incorporating both genome-scale data for cancer subtype identification and experimental models for therapeutic target discovery.
It is an object of the present invention to facilitate the development of better prognostic and therapeutic strategies which will benefit cancer patients with novel treatment options and to improve the overall survival.